This disclosure relates generally to the field of cache coherency, and more particularly to determining whether fetched data will be included in a read-set within a transactional memory environment.
The number of central processing unit (CPU) cores on a chip and the number of CPU cores connected to a shared memory continues to grow significantly to support growing workload capacity demand. The increasing number of CPUs cooperating to process the same workloads puts a significant burden on software scalability; for example, shared queues or data-structures protected by traditional semaphores become hot spots and lead to sub-linear n-way scaling curves. Traditionally this has been countered by implementing finer-grained locking in software, and with lower latency/higher bandwidth interconnects in hardware. Implementing fine-grained locking to improve software scalability can be very complicated and error-prone, and at today's CPU frequencies, the latencies of hardware interconnects are limited by the physical dimension of the chips and systems, and by the speed of light.
Implementations of hardware Transactional Memory (HTM, or in this discussion, simply TM) have been introduced, wherein a group of instructions—called a transaction—operate in an atomic manner on a data structure in memory, as viewed by other central processing units (CPUs) and the I/O subsystem (atomic operation is also known as “block concurrent” or “serialized” in other literature). The transaction executes optimistically without obtaining a lock, but may need to abort and retry the transaction execution if an operation, of the executing transaction, on a memory location conflicts with another operation on the same memory location. Previously, software transactional memory implementations have been proposed to support software Transactional Memory (TM). However, hardware TM can provide improved performance aspects and ease of use over software TM.